41EIPT Cloud-Based Time Series Analysis of Extremes: Use Cases and Applications

Extreme weather events, such as hurricanes, tornadoes, floods, droughts, heatwaves, and blizzards, can cause widespread damage, disrupting ecosystems, agricultural production, and economies. The frequency and intensity of these events have been increasing, likely due to climate change, raising concerns and the need for more accurate analysis and predictions.

NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) has migrated its long-term historical precipitation datasets into the cloud, including that from MERRA-2 reanalysis, GLDAS land data assimilation, and IMERG satellite observations. This cloud-stored data enables scientists and researchers to utilize cloud computing for advanced modeling and forecasting of extreme weather events, eliminating the need to download large datasets.

In this presentation, we will provide an overview of the cloud-based data and services managed by GES DISC; demonstrate methods for accessing and analyzing time series data stored in the cloud; and compare results across various datasets to address critical questions related to extreme precipitation. We will present use cases including:

1. Determining the average total precipitation in California during January and February from 2000 to 2024, and identifying anomalous precipitation in 2021.

2. Calculating the 10, 20, 50, and 100-year return periods for maximum daily rainfall based on 25 years of historical precipitation data (2000-2024) for Maryland.